Triple

T3713271
Position Surface form Disambiguated ID Type / Status
Subject Murmansk Oblast E81464 entity
Predicate hasPortCity P2745 FINISHED
Object Murmansk E100111 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Murmansk | Statement: [Murmansk Oblast, hasPortCity, Murmansk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murmansk
Context triple: [Murmansk Oblast, hasPortCity, Murmansk]
  • A. Murmansk chosen
    Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
  • B. Arkhangelsk
    Arkhangelsk is a historic port city in northern Russia on the White Sea, long serving as a key maritime gateway and administrative center of the surrounding region.
  • C. Severodvinsk
    Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • D. Kirkenes
    Kirkenes is a remote Arctic town in northeastern Norway, near the Russian border, known for its Barents Sea port, winter tourism, and role as a gateway to the far north.
  • E. Severomorsk
    Severomorsk is a closed naval town in Russia’s Murmansk Oblast that serves as the main base of the Russian (formerly Soviet) Northern Fleet on the Barents Sea.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad8b1a81588190b3f27a5483bb610e completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc9cbc5648190936f93868086167e completed March 8, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb02366881909d984b54bfc571e9 completed March 14, 2026, 6:06 a.m.
Created at: March 8, 2026, 3:33 p.m.